Prevalence of peripheral arterial disease in type 2 diabetes mellitus and its correlation with coronary artery disease and its risk factors

Abstract

Peripheral arterial disease (PAD) is one of the macrovascular complications of type 2 diabetes mellitus. Unlike other complications, it has received little attention in the Indian medical literature. There is significant difference in the reported prevalence of PAD and its associated risk factors between Indian and Western studies. In order to assess PAD in diabetics, its associated risk factors and its relationship with coronary artery disease, we conducted a hospital-based, cross-sectional study.
Consecutive patients on regular follow up in our diabetes clinic were included. In addition to a detailed history and physical examination, anthropometric parameters like body mass index, waist circumference and waist hip ratio were measured. Relevant laboratory investigations were performed. Modified Rose questionnaire and Minnesota codes were used to diagnose coronary artery disease (CAD). Colour Doppler examination of the arteries of the lower limbs was performed. Arteries were evaluated both longitudinally and transversely. Individual ABI was obtained for each leg by dividing corresponding ankle pressure by the brachial pressure. The lower of the values obtained for the two legs was taken as the true ABI. A cut off of < 0.9 was used to define peripheral arterial disease. Predictors of PAD were assessed using univariate tests of significance. Binary logistic regression was used to identify independent predictors of CAD.
We studied 146 patients (79 men and 67 women; mean age 59.4 +/- 7.2 years; mean duration of diabetes 8.8 +/- 3.8 years). The prevalence of PAD was 14.4% with women having a slightly higher prevalence (14.9%), as compared to men (13.9%) (p=0.864). CAD was present in 28%. Age, duration of diabetes, smoking, systolic and diastolic blood pressures and an HbA1c >7% were significant predictors of PAD. We did not find a correlation between measures of obesity and PAD. Using binary logistic regression, older age (p=0.01), higher HbA1c levels (p=0.02), microalbuminuria (p=0.03) and deranged lipid profile (total cholesterol, HDL, triglycerides) were found to be significant predictors of CAD.
Using ankle brachial index, we found evidence of PAD in 14.3% of type 2 diabetics. Risk factors significantly associated with PAD were--higher age, longer duration of diabetes, higher systolic and diastolic blood pressure, smoking, higher HbA1c levels and CAD. The prevalence of CAD was higher in patients with PAD (52.38% vs. 24% in those without PAD; p=0.007). Thus the presence of PAD should alert the clinician to a high probability of underlying CAD.

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28 © JAPI • JU LY 2012 • VOL. 60
Abstract
Objectives : Peripheral arterial disease (PAD) is one of the macrovascular complications of type 2 diabetes mellitus.
Unlike other complications, it has received little attention in the Indian medical literature. There is significant
difference in the reported prevalence of PAD and its associated risk factors between Indian and Western studies.
In order to assess PAD in diabetics, its associated risk factors and its relationship with coronary artery disease,
we conducted a hospital-based, cross-sectional study.
Methods: Consecutive patients on regular follow up in our diabetes clinic were included. In addition to a detailed
history and physical examination, anthropometric parameters like body mass index, waist circumference and
waist hip ratio were measured. Relevant laboratory investigations were performed. Modified Rose questionnaire
and Minnesota codes were used to diagnose coronary artery disease (CAD). Colour Doppler examination of
the arteries of the lower limbs was performed. Arteries were evaluated both longitudinally and transversely.
Individual ABI was obtained for each leg by dividing corresponding ankle pressure by the brachial pressure.
The lower of the values obtained for the two legs was taken as the true ABI. A cut off of < 0.9 was used to define
peripheral arterial disease. Predictors of PAD were assessed using univariate tests of significance. Binary logistic
regression was used to identify independent predictors of CAD.
Results: We studied 146 patients (79 men and 67 women; mean age 59.4 ± 7.2 years; mean duration of diabetes
8.8 ± 3.8 years). The prevalence of PAD was 14.4% with women having a slightly higher prevalence (14.9%), as
compared to men (13.9%) (p=0.864). CAD was present in 28%. Age, duration of diabetes, smoking, systolic and
diastolic blood pressures and an HbA1c >7% were significant predictors of PAD. We did not find a correlation
between measures of obesity and PAD. Using binary logistic regression, older age (p=0.01), higher HbA1C levels
(p=0.02), microalbuminuria (p=0.03) and deranged lipid profile (total cholesterol, HDL, triglycerides) were found
to be significant predictors of CAD.
Conclusion: Using ankle brachial index, we found evidence of PAD in 14.3% of type 2 diabetics. Risk factors
significantly associated with PAD were - higher age, longer duration of diabetes, higher systolic and diastolic
blood pressure, smoking, higher HbA1C levels and CAD. The prevalence of CAD was higher in patients with
PAD (52.38% vs 24% in those without PAD; p=0.007). Thus the presence of PAD should alert the clinician to a
high probability of underlying CAD.
*Head, Department of Medicine and Dean, **Academic Junior Resident
(3rd year), Department of Medicine, ***Associate Professor, Department
of Medicine, ****Professor, Department of Radiodiagnosis, *****Senior
Research Associate, ******Senior Resident, Department of Medicine,
PGIMER and Dr R M L Hospital, New Delhi – 110001
Received Date: 28.12.2010; Accepted Date : 10.10.2011
Introduction
Peripheral arterial disease (PAD) is characterized by
atherosclerotic occlusive disease of the lower extremities and
is a marker for atherothrombotic disease in other vascular beds.1
The prevalence of peripheral arterial disease (PAD) in diabetic
patients was found to be 3.2% in a study from South lndia2 and
as high as 15.9% in a western population.3 This reportedly low
prevalence of PAD in South India is in marked contrast to the
high prevalence rate of coronary artery disease (CAD).2,3
A reliable diagnosis of PAD can be made using the
ankle-brachial index (ABI). This simple, painless and highly
reproducible test can be performed in a physician’s oce and
requires only a blood pressure apparatus and a hand-held,
continuous-wave doppler probe.
The focus of the vascular complications of diabetes has been
on coronary artery disease and nephropathy while peripheral
vascular disease has largely been ignored, especially in India.
Hence, we carried out the present study to assess the prevalence
of PAD in type 2 diabetes by measuring ankle brachial
index
using duplex Doppler ultrasound of the lower limbs and to
correlate it with various risk factors. We also sought to evaluate
the relationship between PAD and CAD in those with type 2
diabetes.
Methods
Consecutive patients with type 2 diabetes mellitus aending
the Diabetes clinic in the Department of Medicine at PGIMER
and Dr. Ram Manohar Lohia Hospital, New Delhi for at least
six months were recruited for the study. Each patient gave
Original Article
Prevalence of Peripheral Arterial Disease in Type 2
Diabetes Mellitus and its Correlation with Coronary
Artery Disease and its Risk Factors
AK Agarwal*, Manjeet Singh**, Vivek Arya***, Umesh Garga****, Vivek Pal Singh*****,
Vineet Jain******

© JAPI • JU LY 2012 • V OL. 60 29
legs was taken as the true ABI.8 An ABI of < 0.9 was dened as a
low ABI indicative of peripheral arterial disease.
CAD was diagnosed by a history of angina (Modied Rose
questionnaire), ECG changes (Minnesota codes), or any past
history of CAD or any treatment given for CAD.6
Smoking status was dened as :Smoker: smoking ≥ 1 cigaree/
bidi per day at the time of the study or quit smoking < 10 years
back and non-smoker: never smoked/left smoking for ≥10 years.
Statistics
Continuous data are presented as means and standard
deviations and categorical data as proportions. The dierences
between patients with and without PAD in terms of risk factors
were assessed using Student’s t test for continuous variables
and chi square test for dichotomous variables. Binary logistic
regression was used to evaluate independent predictors of CAD.
Results
A total of 146 patients (79 men and 67 women) with type 2
diabetes were included in the study. Demographic and clinical
features of these patients are shown in Table 1.
The age of the patients ranged from 39 to 80 years with a
mean age of 59 years. The duration of diabetes ranged from 1
to 25 years with a mean of 8.8 years. More than half the patients
(52.7%) were hypertensive and very few (2.7%) smoked.
The mean systolic blood pressure was 136 ± 11 mm Hg and
mean diastolic blood pressure was 86 ± 5 mm Hg. BMI ranged
from 16.2 – 37.3 kg/m2 with mean BMI being 26.24 ± 3.8 kg/m2.
Men had a higher mean Waist hip ratio (0.96 ± 0.08) than women
(0.89 ± 0.07) (p < .001).
Most patients had fairly good blood glucose control (mean
HbA1c 7.1 ± 0.9 %). However, diabetic control as measured by
FBG, PPBG and HbA1C was beer in men than in women. This
dierence was signicant only for PPBG which was higher in
women (mean 222.8 ± 79.2) than in men (189.4 ± 57) (p=0.005).
CAD, as assessed by the Rose questionnaire and Minnesota
codes, was present in 28% of patients (26.5% of men and 29% of
women; p=0.66). The prevalence of risk factors for CAD in the
study group is shown in Table 2.
Based on ABI, the prevalence of PAD was found in 21
patients out of 146 (14.4%) with women having a slightly higher
prevalence (10 out of 67; 14.9%), as compared to men (11 out of
79; 13.9%) (p=0.864).
Of those with PAD, 6 patients (28.6%) were symptomatic. The
wrien, informed consent to participate in the study and the
study protocol was approved by the institutional review board
including ethical issues.
Inclusion criteria for the study
1. A diagnosis of type 2 diabetes mellitus as per WHO criteria.
2. Treatment with dietary restrictions and / or oral
hypoglycaemic agents and / or insulin for at least 6 months.
Patients with the following conditions, which would
interfere with the measurement of the ankle brachial index,
were excluded:
1. Trauma, surgery or amputation involving the lower limb
2. Leg ulcers
3. Deep vein thrombosis
4. Filariasis or lower limb swelling due to other causes which
would impair Doppler image quality.
A detailed history was obtained from each patient. This
included age, sex, smoking, alcohol intake, diabetes mellitus
– duration, treatment; hypertension – duration, treatment;
symptoms of coronary artery disease; family history of diabetes,
coronary artery disease, hypertension or cerebrovascular
accident.
Each patient was examined with particular aention to blood
pressure (as per JNC7 criteria),4 body mass index (weight (kg) /
height (metre)2) and central obesity (dened as a waist hip ratio
of > 0.85 in females and > 0.95 in males).
Investigations performed included a resting 12-lead
electrocardiogram recorded as per WHO recommendations,6
fasting and post-prandial blood glucose, blood urea, serum
creatinine, uric acid, total and HDL cholesterol, triglycerides
and glycated hemoglobin (HbA1c). Values for VLDL and
LDL cholesterol were calculated using Friedewald’s method7.
Microalbuminuria (30-300 mg of albumin excretion per day) was
assessed using the immunoturbidimetric assay.
Colour Doppler scan: The arteries of the lower limbs were
assessed using a general purpose linear probe with image
frequency of 5.7-10.0 Mhz. Arteries were evaluated both
longitudinally and transversely by ALT 3500 HDL ultrasound
machine (M/S Phillips). With patients in the supine position,
brachial artery systolic pressure was rst measured by palpatory
method and then by Doppler blood ow method in both arms.
Similarly, ankle blood pressure was measured by palpatory
method with the cu placed just above the ankle and then by
measuring Doppler blood ow in the dorsalis pedis artery or the
posterior tibial artery of both feet. Individual ABI was obtained
for each leg by dividing corresponding ankle pressure by the
brachial pressure. The lower of the values obtained for the two
Table 1 : Demographic and clinical prole of patients in the
study group
Men
(n=79)
Women
(n=67)
Total
(n=146)
Age (years) (Mean ± SD) 60 ± 7 58 ± 7 59 ± 7
Duration of diabetes (years) (Mean
± SD) 9.2 ± 3.9 8.3 ± 3.6 8.8 ± 3.8
History of hypertension 41 (51.90 ) 36 (53.7 ) 77 (52.7 )
Family history of diabetes 40 (50.6 ) 44 (65.7 ) 84 (57.5 )
Smoking 4 (5.06 ) 0 (0 ) 4 (2.7)
Note: Figures in parentheses are percentages.
None of the dierences between men and women was statistically signicant.
Table 2: Prevalence of cardiovascular risk factors in the
study group
Risk factor N (%)
Hypertension 77 (52.74)
Smoking 4 (2.74)
Family history of diabetes 84 (57.53)
BMI >23Kg/m2113 (77.40)
BMI>25Kg/ m282 (56.16)
Central obesity 88 (60.27)
HbA1C >7% 70 (47.95)
Serum total cholesterol >200 mg / dl 57 (39.04)
Serum LDL >140 mg / dl 34 (23.29)
Serum HDL cholesterol < 40 mg / dl 93 (63.70)
Serum triglycerides > 150 mg / dl 41 (28.08)
Microalbuminria/Albuminuria (mg / 24 hrs.) 44 (30.14 )

30 © JAPI • JU LY 2012 • VOL. 60
most common symptom was intermient claudication which was
present in all symptomatic patients. None of our patients gave
a history of nocturnal pain or a cold sensation in the feet. On
clinical examination, 3 patients (14.3%) had decreased peripheral
pulses. However, none of the patients had ulcers, gangrene, skin
changes or dependent pallor.
Some of the typical ndings on Doppler ultrasound are shown
in Figures 1A, 1B, 1C and 1D.
The dierences between the PAD and the non-PAD groups
in terms of risk factors were assessed using Student’s t test for
continuous variables and chi square test for discrete variables.
These results are summarized in Table 3.
Of the 21 patients with PAD, 11 (52.38%) had CAD. Of the
remaining 125 patients without evidence of PAD, 30 (24%) had
CAD. This dierence was statistically signicant by the chi
square test (p=0.007).
Age, duration of diabetes, systolic BP, diastolic BP and
HbA1C >7% were found to be signicantly dierent between the
two groups. On comparing the use of ACE inhibitors, statins,
insulin, sulphonylureas, metformin and pioglitazone between
those with and those without PAD, no statistically signicant
dierences were found.
Binary logistic regression (Table 4) was used to assess
signicant independent predictors of CAD. Older age (p=0.01),
higher HbA1C levels (p=0.02), microalbuminuria (p=0.03) and
deranged lipid prole (total cholesterol, HDL, triglycerides)
were found to be signicant predictors of CAD.
Discussion
In this cross-sectional study on 146 type 2 diabetes patients,
the mean age was 59.4 ± 7.2 years and the mean duration of
diabetes was 8.8 ± 3.8 years. The group had 2.74% smokers,
57.5% of patients gave a positive family history of diabetes and
52.7% were hypertensive.
The prevalence of PAD as detected by Doppler ultrasound
(ABI) was 14.4 %. Previous studies by Marinelli et al,
10
J
anka et al,
3
Walters et al,
11
Migdalis et al
12
and the Fremantle diabetes study
by Paul et al
13
found the prevalence of
PAD to be 33%, 15.9%,
23.5%, 44% and 13.6%, respectively.
Few Indian studies have assessed PAD in diabetics. Two large
studies from South India, namely, by Mohan et al
14
(n=4941) and
CUPS2 (n=1262) found a prevalence of PAD in diabetics to be
3.9% and 6.3%, respectively. CUPS, a community based study,
Fig. 1a : Longitudinal scan of a lower limb artery showing a plaque
(arrow). The red area shows blood ow signal.
Fig. 1b : Lower limb artery showing intimal thickening with
calcied plaques.
Fig. 1c : Decreased ow in the anterior tibial artery.
Fig. 1d : Absent ow in the dorsalis pedis artery.

© JAPI • JU LY 2012 • V OL. 60 31
Table 3: Cardiovascular disease risk factors in PAD and non-PAD subgroups.
Risk factor Non-PAD PAD P value
Age (years) Mean + SD 58 ± 6 67 ± 7 0.001
Duration of diabetes (years) Mean + SD 8 ± 3 12 ± 5 0.001
Hypertension 63 (50.4) 14 (66.7) 0.169
Smoking 2 (1.6) 2 (9.5) 0.1
CAD 30 (24) 11 (52.38) 0.007
SBP (mmHg) 135 ±10 144 ± 10 0.001
DBP (mmHg) 86 ± 0.5 89 ± 5 0.005
BMI (Kg/m2) 26.23 ±3.79 26.26 ±3.60 0.977
Waist Hip Ratio 0.93 ±0.08 0.92 ±0.11 0.754
Fasting blood glucose (mg%) 144 ± 47 147 ± 60 0.833
Post–prandial blood glucose (mg%) 205 ± 68 200 ± 77 0.748
Total cholesterol (mg%) 182 ± 43 180 ± 43 0.893
Serum LDL (mg%) 108 ± 41 116 ± 54 0.448
Serum HDL (mg%) 47 ± 16 43 ± 11 0.187
Serum triglycerides (mg%) 129 ± 62 125 ± 44 0.770
HbA1C (%) 6.9 ± 0.9 7.7 ± 0.9 0.001
Urinary microalbuminuria/albuminuria mg / 24 hrs. 68 ± 254 24 ± 19 0.468
Note: Figures in parentheses are percentages. BMI = body mass index; SBP = systolic blood pressure DBP= diastolic blood pressure CAD = coronary artery
disease
Table 4: Binary logistic regression to assess independent
predictors of CAD.
Variable Regression coecient p value
Sex 0.75 0.46
Age 0.22 0.01
BMI 0.17 0.29
Waist hip
Ratio -13.44 0.05
Family h/o diabetes -0.02 0.98
Duration of diabetes 0.33 0.20
Smoking -3.18 0.20
Hypertension 0.31 0.69
HbA1C 4.31 0.02
Total cholesterol 0.12 0.01
LDL cholesterol -0.01 0.32
HDL cholesterol -0.13 0.02
Triglycerides -0.02 0.04
Microalbuminuria -0.09 0.03
Waist circumference 0.11 0.20
PAD -2.55 0.10
found a lower prevalence of PAD than our study which was
hospital based.
Two recent studies from North India, one by Agrawal et
al15 (n=4400) and the other by Madhu et al16 (n=364) found
the prevalence of PAD in diabetics to be 18.1% and 13.73%,
respectively. The former study was performed on outpatients
with a study design similar to ours.
In the Fremantle diabetes study,
age, duration of diabetes,
higher systolic blood pressure and higher BMI were found to
be signicant predictors of PAD.13 In the study by Agrawal et
al a signicant correlation was found between age,duration of
diabetes and prevalence of PAD.15 In both CUPS2 and in the
study by Mohan et al14 age and higher systolic blood pressure
predicted PAD.2 Systolic blood pressure was also shown to be a
predictor of PAD in the study by Janka et al.
3
In our study, both age and duration of diabetes were
signicant predictors of PAD. The prevalence of hypertension
was 50% in patients without PAD as compared to 66% in those
with PAD. Mean systolic blood pressure was 134 ± 10 in the non
– PAD group as compared to 144 ± 10 in the PAD group (p <.05).
We did not nd a correlation between obesity and PAD.
Other Indian studies (CUPS2, Agrawal et al15) also failed to nd
such a correlation.
The majority of our patients had well-controlled diabetes.
The mean HbA1c was 7.0 ± 0.9%. On comparing the two groups,
mean HbA1c was 6.9 ± 0.9 % in the non-PAD group as compared
to 7.7 ± 0.9 in the PAD group (p<0.05). Using a cut o level of >7
mg% for poor control, 44% had poor glycaemic control in the
non-PAD group compared to 71.43% in the PAD group. Studies
by Walters et al
11
and Janka et al
3
also found inferior glycemic
control to be a predictor of PAD.
We found no signicant dierences between serum total
cholesterol, LDL cholesterol, HDL cholesterol or triglyceride
levels between the PAD and the non-PAD subgroups. Some
previous studies, like those by Walters et al
11
and Mohan et al,
14
found serum total cholesterol levels to be one of the predictive
factors for PAD.
There was a higher prevalence of smoking in those with PAD
(9.52% vs 1.60% in those without PAD). However, the overall
prevalence of smoking was very low (2.74%). In the Fremantle
diabetes study, smoking was found to be more prevalent in the
PAD group than in the non-PAD group (24% vs 12.6%) and it
was found to be signicantly associated with PAD.13 Given the
low prevalence of smoking in our study, its correlation with
PAD is dicult to assess.
The prevalence of CAD was 52.38% in PAD patients and 24%
in non-PAD patients (p= 0.007). The odds ratio for CAD were
3.48 with a relative risk of 1.59.
Similarly, the Cardiovascular Health study, a prospective
study to evaluate the association of PAD and CAD, enrolled 5,888
participants above 65 years of age.17 The crude mortality rate at
6 years was highest (32.3%) in those with prevalent CAD and a
low ABI, and lowest in those with neither of these ndings (8.7%).
In the CUPS study the prevalence of CAD was not found to be

32 © JAPI • JU LY 2012 • VOL. 60
signicantly higher in those with PAD.2 However, Krishaswamy
et al found that PAD was common in elderly South Indian
patients with coronary artery disease.18 PAD was found in 19
out of 80 patients above the age of 60 (23.7 %).
Leng et al evaluated 1,592 subjects aged 55-74 years for the
presence of peripheral arterial disease and classied them as
claudicants, major and minor asymptomatic patients.19
Deaths from cardiovascular disease were more likely in both
claudicants and subjects with major or minor asymptomatic
disease.
Mckenna et al evaluated 744 patients for lower extremity
peripheral arterial disease (PAD). Using an ABI of less than 0.85
as the cut o, the relative risk (RR) for total mortality associated
with PAD was 2.36 (95% CI 1.60- 3.48) after adjusting for baseline
covariates in a proportional hazards model.20
Using binary logistic regression signicant independent
predictors of CAD were: older age (p=0.01), higher HbA1c levels
(p=0.02), microalbuminuria (p=0.03) and deranged lipid prole
(high total cholesterol, LDL and triglyceride levels as well as
low HDL levels).
Conclusions
Using Ankle brachial index, we found evidence of PAD in
14.3% of type 2 diabetics. Risk factors signicantly associated
with PAD were higher age, longer duration of diabetes, systolic
and diastolic blood pressure, smoking, HbA1C and CAD. We also
found a higher prevalence of CAD in patients with PAD (52.38%
vs 24% in those without PAD). This nding suggests that all
patients diagnosed to have PAD should be carefully evaluated
for coronary artery disease.
Further studies, with a larger sample size, are needed to
investigate the possible mechanisms linking PAD and CAD
and to determine whether PAD predicts the development and
progression of CAD.
Acknowledgement
We are grateful to Dr (Prof.) N K Chaturvedi, Medical
Superintendent and Director, PGIMER, Dr R M L Hospital for
facilitating the study. The authors are thankful to Dr (Prof.)
Rajbala Yadav , HOD, Labs, at the institute for her help.
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